Informatics in Education

In a previous publication we examined the connections between high-school computer science (CS) and computing higher education. The results were promising—students who were exposed to computing in high school were more likely to take one of the computing disciplines. However, these correlations were not necessarily causal. Possibly those students who took CS courses, and especially high-level CS courses in high school, were already a priori inclined to pursue computing education. This uncertainty led us to pursue the current research. We aimed at finding those factors that induced students to choose CS at high school and later at higher-education institutes. We present quantitative findings obtained from analyzing freshmen computing students' responses to a designated questionnaire. The findings show that not only did high-school CS studies have a major impact on students’ choice whether to study computing in higher education—it may have also improved their view of the discipline.

Computer science concepts have an important part in other subjects and thinking computationally is being recognized as an important skill for everyone, which leads to the increasing interest in developing computational thinking (CT) as early as at the comprehensive school level. Therefore, research is needed to have a common understanding of CT skills and develop a model to describe the dimensions of CT. Through a systematic literature review, using the EBSCO Discovery Service and the ACM Digital Library search, this paper presents an overview of the dimensions of CT defined in scientific papers. A model for developing CT skills in three stages is proposed: i) defining the problem, ii) solving the problem, and iii) analyzing the solution. Those three stages consist of ten CT skills: problem formulation, abstraction, problem reformulation, decomposition, data collection and analysis, algorithmic design, parallelization and iteration, automation, generalization, and evaluation.

The Lithuanian Informatics Olympiad is a problem solving contest for high school students. The work of each contestant is evaluated in terms of several criteria, where each criterion is measured according to its own scale (but the same scale for each contestant). Several jury members are involved in the evaluation. This paper analyses the problem how to calculate the aggregated score for whole submission in the above mentioned situation. The chosen methodology for solving this problem is Multiple Criteria Decision Analysis (MCDA). The outcome of this paper is the score aggregation method proposed to be applied in LitIO developed using MCDA approaches.

The Lithuanian Informatics Olympiads (LitIO) is a problem solving programming contest for students in secondary education. The work of the student to be evaluated is an algorithm designed by the student and implemented as a working program. The current evaluation process involves both automated (for correctness and performance of programs with the given input data) and manual (for programming style, written motivation of an algorithm) grading. However, it is based on tradition and has not been scientifically discussed and motivated. To create an improved and motivated evaluation model, we put together a questionnaire and asked a group of foreign and Lithuanian experts having experience in various informatics contests to respond. We identified two basic directions in the suggested evaluation models and made a choice based on the goals of LitIO. While designing the model in the paper, we reflected on the suggestions and opinions of the experts as much as possible, even if they were not included into the proposed model. The paper presents the final outcome of this work, the proposed evaluation model for the Lithuanian Informatics Olympiads.

Individuals vary across many dimensions due to the effects of gender-based, personality, and cultural differences. Consequently, programming contests with a limited and restrictive structure (e.g., scoring system, questioning style) are most favourable and attractive to a specific set of individuals with the characteristics that best match this structure. We suggest that a more inclusive and flexible structure will allow contests to be more appealing to a wider range of participants by being less biased towards specific traits. As well, by making contests more broadly appealing, they become better post secondary recruiting tools that can potentially be used to attract under-represented populations to the discipline of computer science. In this paper, we focus on gender-based differences and the effect of a competition's structure on female participants.